An effective document image deblurring algorithm

Authors:
Xiaogang Chen; Xiangjian He; Jie Yang; Qiang Wu
Affiliations:
Inst. of Image Process. & Pattern Recognition, Shanghai Jiao Tong Univ., Shanghai, China;Centre for Innovation in IT Services & Applic., Univ. of Technol., Sydney, NSW, Australia;Inst. of Image Process. & Pattern Recognition, Shanghai Jiao Tong Univ., Shanghai, China;Centre for Innovation in IT Services & Applic., Univ. of Technol., Sydney, NSW, Australia
Venue:
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Year:
2011

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Abstract

Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct characteristics of document images are investigated. We propose a content-aware prior for document image deblurring. It is based on document image foreground segmentation. Besides, an upper-bound constraint combined with total variation based method is proposed to suppress the rings in the deblurred image. Comparing with the traditional general purpose deblurring methods, the proposed deblurring algorithm can produce more pleasing results on document images. Encouraging experimental results demonstrate the efficacy of the proposed method.